Collaborative Research: CNS Core: Medium: Parallel and Real-Time Multicore Scheduling for an Efficiently-Used Cache (PARSEC)

具有严格“实时”要求的安全关键型系统正变得越来越普遍和复杂。最新的复杂实时系统趋势的缩影是自动车辆，它必须同时并以最小的延迟执行图像识别、机器学习、路线选择和规划任务。此外，由于对整个系统的大小、重量和功率的严格限制，这些实时计算任务必须在共享硬件(例如，处理器、存储器、存储)上执行；然而，计算机资源的共享在任务之间产生了巨大的竞争和竞争。该项目解决了一个根本挑战，即多个实时、安全关键的任务如何有效地共享底层内存体系结构，同时仍然满足时间限制。特别是，该项目将开发一个新的系统设计和分析框架，称为PARSEC(高效使用缓存的并行和实时多核调度)。PARSEC通过(A)明确管理竞争任务如何共享内存资源的新的多核调度算法；(B)验证系统的时间限制是否满足现有内存资源的新的形式分析技术；以及(C)一组开放源码的自动化工具，使系统设计人员能够在商业现成的处理架构上利用该框架，从而为最先进的技术做出贡献。PARSEC将在流行的RISC V架构上实施和评估，以促进向公众广泛传播。该项目将导致更安全、更高效的时间敏感型系统设计，包括自动驾驶车辆和机器人。此外，本项目中的研究和系统设计技术可应用于在共享处理器和内存上执行并发计算任务的任何实时、安全关键系统。从项目人工制品获得的内存层次中的争用减少将潜在地减少对安全关键系统的电力和燃料的需求，减少它们的碳足迹。该项目将通过与安全关键系统设计相关的课程项目，为本科生和研究生提供独特的培训、教育和体验式学习机会，从而使内华达大学拉斯维加斯分校和韦恩州立大学的教育使命受益。为了帮助其他研究人员，该项目还将通过出版物、公开演讲、教程、项目网站和在线视频传播研究成果。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Safety-critical systems that have strict “real-time” requirements are becoming increasingly ubiquitous and complex. Epitomizing this recent trend toward sophisticated real-time systems are autonomous vehicles, which must perform image recognition, machine learning, routing, and planning tasks, simultaneously and with minimal delay. Furthermore, these real-time computational tasks must execute upon shared hardware (e.g., processors, memory, storage) due to the severe constraints on the size, weight, and power of the entire system; however, the sharing of computer resources creates tremendous contention and competition between tasks. This project addresses a fundamental challenge of how multiple real-time, safety-critical tasks can effectively share the underlying memory architecture and still meet timing constraints. In particular, this project will develop a novel system design and analysis framework called PARSEC (Parallel and Real-Time Multicore Scheduling for an Efficiently-Used Cache). PARSEC contributes to the state-of-the-art with (a) new multicore scheduling algorithms that explicitly manage how contending tasks share memory resources; (b) new formal analysis techniques that verify that a system’s timing constraints are satisfied with existing memory resources; and (c) a set of open-source automated tools that will enable system designers to utilize the framework on commercial off-the-shelf processing architectures. PARSEC will be implemented and evaluated upon the popular RISC V architecture to facilitate wide dissemination to the public.This project will result in safer, more efficient designs of time-sensitive systems, including autonomous vehicles and robotics. Furthermore, the resulting research and system design techniques in this project can be applied to any real-time, safety-critical systems executing concurrent computational tasks upon a shared processor and memory. The reduction in contention in the memory hierarchy obtained from project artifacts will potentially lessen demands on power and fuel in safety-critical systems, decreasing their carbon footprint. The project will benefit the educational missions of University of Nevada Las Vegas and Wayne State University by providing a unique training, education, and experiential learning opportunity for undergraduate and graduate students via course projects related to safety-critical system design. To aid other researchers, this project will also disseminate research results through publications, public talks, tutorials, project websites, and online videos.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.